A Method for Eliminating or Qualifying Known Objects Using Background Stars and Other Objects

We have experienced a regularly occurring problem when reviewing video footage of flying objects. The problem is that conventional monoscopic
videography does not provide a means to determine the size, distance or velocity of an object. Because of this it is easily argued that the same
object could be small, close to the camera, and slow (such as a bird or model), large, fast, and far away (such as a fighter jet), or even larger and
traveling at unconventional velocities. I have witnessed this debate go back and forth tirelessly on many threads and I believe that many of these
debates have been unnecessary.

I propose that there is a multi-step mathematical way to eliminate or qualify known objects based on size, distance and velocity. This is possible so
long as within the frame, at some point, there is a known star constellation or other object of known size.

This method is based on the acquisition and conversion of the angular size of objects in the video. For the example provided here we will presume
that the time, location, and direction of the observation has been acquired from the observer so that we are dealing with a known star field.

In the image below we have a hypothetical constellation of which the observed object in the video has passed near by.

Because the star field is known, so is the angular distance between any 2 stars. For the sake of illustration we will use 2 stars that span the
majority of the frame for our measurements.
Stars A and B are known to have an angular separation of 16.47 degrees.

We will first test for the possibility that the objects are Canada geese flying in formation. We know that Canada geese have a wingspan of
approximately 2 meters. The objects according to our star field reference are about 0.38 of a degree across.

This would put geese about 302 meters away from the camera. Observing the video we find that the object covers the distance between stars A and B in
0.6 seconds. Again the angular distance between those 2 stars is known to be 16.47 degrees. At 302 meters from the camera this translates to 87
meters. 87 meters in 0.6 seconds is 522 kilometers per hour. This velocity eliminates Canada geese (which have a maximum speed of about 90
kilometers per hour) as a possible solution for these objects.

Using the above information lets test for F-18 Hornet fighter Jets flying in formation. F-18s have a wingspan of 12.3 meters. Given the angular size
in the image, this would put the aircraft at 1.85 kilometers from the camera. At this distance the angular distance between star A and star B would
equal 536 meters. 536 meters in .6 seconds is equivalent to 3216 kilometers per hour. The maximum speed of an F-18 is 1915 kilometers per hour and
that is at an altitude of 12 000 meters. This eliminates the F-18 as a possible solution for these objects.

One more example. We will theorize that the objects are the navigation lights of an aircraft approximately the size of an F-117 Night Hawk stealth
fighter which has a length of 20.9 meters.

Using our reference stars as a ruler again the total angular size of the formation of objects is 1.84 degrees. This would put such an aircraft at a
distance of 651 meters from the camera. At 651 meters 16.47 degrees is equivalent to 188 meters. 188 meters in 0.6 seconds is equivalent to 0.95
Mach. This velocity is well within the performance capabilities of some conventional jet aircraft and thus qualifies as a possible solution.

It should be added that other performance characteristics can be gauged from this method such as g-loading during turns, and whether or not a
conventional craft would be close enough to be heard, etc.

This is a simplified example of this method and further enhancements to accuracy can be implemented such a accounting for light source blooming and
calibration of the cameras frame rate, etc.

I would be happy to hear from those of you who have corrections, criticisms and possible additions.

Your method is a good idea and could be useful in some cases IMHO, but it has one fatal flaw unless I'm overlooking something...

Without having precise and synchronized observations made at two separate locations separated by significant distance, you can't gauge
altitude unless you know the size of your UFO.

In the vast majority of cases a UFO sighing is a light (or lights), which may bear no resemblance to the actual size of an object, and even if they
did, most footage is probably going to be useless for gaging the size of objects in the dark at a distance.

In order to make your idea (it's actually not a new one - people have been using a similar idea for decades if not centuries to calculate the
trajectories of objects seen in the sky) work, you need to make two videos of the same object moving against the background stars at the same time
from your separate locations that are at a known distance from each other, and use triangulation to work out the altitude.

It's getting late now, but I'll try and dig up a few links on the subject and post them here in the next 24 hrs or whenever I get a chance. Good
thread by the way!

The angular size of the object can only be estimated if the image is in focus. There is no way of knowing whether a set of 'lights' is in focus or
not. The vast majority of such photos I've seen are way out of focus. People pull focus to 'expand' the object in order to see detail, which is
completely wrong. The clearest image is always the smallest image. In the vast majority of cases, lights will be dimensionless points. You can't
apply angular measurements to points. This is why the first example of testing for geese is invalid. If these were actually geese in focus, you'd be
able to recognise them as geese. The idea of using the angular distance between two points is valid when you make assumptions about their true spacial
arrangement.

The method does not use pixel size to determine angular size. It does not use pixels at all. I apologize if I have somehow given that impression.
The method uses the limits of sizes of known objects to qualify or eliminate them. The concepts, techniques and math for this method are complicated.
In the introduction to the OP and in one reply already I have explained that this method is not designed to be used for acquiring the size of an
object. I have also given three working examples. I'm sorry if you cannot understand it but there is only so much that can be done to explain it.
Despite this it does not make the method "worthless" to those who can understand and implement it.

You are correct that there are many examples of footage that this method cannot be used with.

I have (amongst many other tools) a spark plug socket in my tool box. In general it can only be used when I need to change the spark plugs in my
vehicle. It is useless for any other task I have, however it is still very handy (and necessary) when the occasion requires.

Most tools in fact have a limited range of use as does the method explained in this thread.

Ok, I have read you reply again and I see that you are arguing that pixel counting cannot be used to determine the size of something. I haven't
argued against this. Then I see in your latest reply that you mention that pixel counting is a valid angular measuring system.
Pixels were never mentioned in the original post and pixels have nothing to do with the topic. I am missing why you are hung up on pixels. I am also
missing why you are hung up on knowing the size of the object in question. This thread has nothing to do with measuring or knowing the actual size of
the object in the video. I'm sorry, your mind seams to be closed around trying to measure the actual size of the object and I can do nothing else to
help you open your mind to this new concept. Perhaps someone else here can explain it in a way that will work for you.

Look, we are not putting you down for trying to come up with something useful, but what you are trying to do is re-invent the wheel using baking dough
as a construction material. It won't work because your idea is flawed.

UFOs are, by definition objects of unknown size. So if you don't know the size or the distance, the only way to find out either/both of these
two things is to use the method I outlined in my previous post to you and to use triangulation/trigonometry to calculate the unknowns.

Don't you think if there was another, easier way, that people would be doing it?

As I said, scientists have been using this method for years to calculate the altitude and velocity of meteors, and the same principals apply to other
objects:

HOW HIGH IS A PERSEID? Perseid meteors seem so nearby when they fly overhead, but appearances can be deceiving. Consider the following fireball,
which lit up the sky above the Marshall Space Flight Center two nights ago:

NASA astronomer Bill Cooke photographed the Perseid using not one but two all-sky cameras located 100 miles apart. The system's wide baseline, which
crosses state lines between Alabama and Georgia, allowed him to triangulate the meteor's position and measure its velocity. "It came in at 58.8 km/s
(130,000 mph) and disintegrated between 111 and 86 km above Earth's surface," he says.

So far, the dual-camera system has captured seven bright Perseids suitable for analysis. Cooke's histograms of starting and ending heights answer the
question, how high is a Perseid?

A successful observation of a meteor consists of two images (photographs) from stations separated by 20km or more [McCrosky, 1965]. This dual
observation data set allows the scientist to determine the true path the meteor will take through the atmosphere, its probable impact location, as
well as its previous heliocentric orbit. Two stations could supply such data sets, as attempted by Harvard in 1936 and Ondrejov in 1951, however
success would be inhibited by the sky coverage limitations of only two stations. Therefore networks of photographic observations stations of greater
than two stations were established (See Table 1) to formally observe the night sky in hopes of acquiring the aforementioned data sets reliably. The
following are the original formal networks (> two stations) that began from 1963 – 1969

I think that people are missing the point of the OP, or maybe I am, but if I understand correctly then this could in fact be a useful tool in
eliminating possibilities or or confirming that something is in fact a possibility.

An example would be the many threads in which strange lights are seen, and debated for pages as to whether the lights are some specific thing. (a jet,
a bird, etc...) If there are a pair of stars that the object moves between then this method can be used to eliminate the possibility of it being said
object, and also give a list of things that it could in fact possibly be.

Notice how the negative pessimist gets all the starts when the open minded Topic Creator barely gets any love. This sums up this site and how
corrupted it is. Nobody with a remotely open minded idea gets any positive feedback but rather some guy who wants to find any way to shut the idea
down and make them feel stupid in the process. You sound like you're arguing that the world must be flat from my perspective.

How do you expect to learn ANYTHING with this kind of backwards thinking? Trying to tell somebody with such a creative and progressive idea that it
will never work because of one plausible flaw is just down right ignorant and trying to prove you're right and they're wrong in the process is just
childish.

What ever happened to pointing out the problems and working towards fixing them? You know, that little word called communication.

Originally posted by Majiq
I think that people are missing the point of the OP, or maybe I am, but if I understand correctly then this could in fact be a useful tool in
eliminating possibilities or or confirming that something is in fact a possibility.

Thank you Majiq, For a bit there I thought I was maybe loosing my grip on sanity. You have grasped this concept and how it works exactly. Like you
say, this method will not tell you what an object is but it will narrow things down and put it in a range of possibilities.

Thank you all for the kind support. I have been working on applying this to a couple of actual cases over the last week and you tipped the balance on
my decision to post the results when they are complete.

waveguide3,
Thanks for the logical analysis and pointing out the limits of the method when used on point sources. I was concerned about that, especially when a
decision has to be made as to whether it is a point source that is poorly resolved or an object with a resolved angular size. I believe the method
can be useful on a point source so long as it is only employed to calculate the minimum velocity of an object based on how far away an object of that
size would have to be in order to be measured as a point source. I opted not to post in the OP about it since I haven't been able to spend time on
confirming it yet. The example I used in the OP eluded to it and so Kudos for noticing! It benchmarks your level of understanding on these types of
things.

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